mirror of
https://github.com/google/nomulus.git
synced 2025-05-13 16:07:15 +02:00
Add a Fibonacci fitter for metrics bucketing
A Fibonacci fitter is useful in situations where you want more precision on the low end than an ExponentialFitter with exponent base 2 provides without the hassle of dealing with non-integer boundaries, such as would be created by an exponential fitter with a base of less than 2. Fibonacci fitters are ideal for integer metrics that are bounded across a certain range, e.g. integers between 1 and 1,000. This also cleans up some unit test comments. ------------- Created by MOE: https://github.com/google/moe MOE_MIGRATED_REVID=156773367
This commit is contained in:
parent
e6af34301d
commit
1adeb57fea
4 changed files with 149 additions and 2 deletions
64
java/google/registry/monitoring/metrics/FibonacciFitter.java
Normal file
64
java/google/registry/monitoring/metrics/FibonacciFitter.java
Normal file
|
@ -0,0 +1,64 @@
|
|||
// Copyright 2017 The Nomulus Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
package google.registry.monitoring.metrics;
|
||||
|
||||
import static com.google.common.base.Preconditions.checkArgument;
|
||||
|
||||
import com.google.auto.value.AutoValue;
|
||||
import com.google.common.collect.ImmutableSortedSet;
|
||||
|
||||
/**
|
||||
* A {@link DistributionFitter} with intervals of increasing size using the Fibonacci sequence.
|
||||
*
|
||||
* <p>A Fibonacci fitter is useful in situations where you want more precision on the low end than
|
||||
* an {@link ExponentialFitter} with exponent base 2 would provide without the hassle of dealing
|
||||
* with non-integer boundaries, such as would be created by an exponential fitter with a base of
|
||||
* less than 2. Fibonacci fitters are ideal for integer metrics that are bounded across a certain
|
||||
* range, e.g. integers between 1 and 1,000.
|
||||
*
|
||||
* <p>The interval boundaries are chosen as {@code (-inf, 0), [0, 1), [1, 2), [2, 3), [3, 5), [5,
|
||||
* 8), [8, 13)}, etc., up to {@code [fibonacciFloor(maxBucketSize), inf)}.
|
||||
*/
|
||||
@AutoValue
|
||||
public abstract class FibonacciFitter implements DistributionFitter {
|
||||
|
||||
/**
|
||||
* Returns a new {@link FibonacciFitter}.
|
||||
*
|
||||
* @param maxBucketSize the maximum bucket size to create (rounded down to the nearest Fibonacci
|
||||
* number)
|
||||
* @throws IllegalArgumentException if {@code maxBucketSize <= 0}
|
||||
*/
|
||||
public static FibonacciFitter create(long maxBucketSize) {
|
||||
checkArgument(maxBucketSize > 0, "maxBucketSize must be greater than 0");
|
||||
|
||||
ImmutableSortedSet.Builder<Double> boundaries = ImmutableSortedSet.naturalOrder();
|
||||
boundaries.add(Double.valueOf(0));
|
||||
long i = 1;
|
||||
long j = 2;
|
||||
long k = 3;
|
||||
while (i <= maxBucketSize) {
|
||||
boundaries.add(Double.valueOf(i));
|
||||
i = j;
|
||||
j = k;
|
||||
k = i + j;
|
||||
}
|
||||
|
||||
return new AutoValue_FibonacciFitter(boundaries.build());
|
||||
}
|
||||
|
||||
@Override
|
||||
public abstract ImmutableSortedSet<Double> boundaries();
|
||||
}
|
Loading…
Add table
Add a link
Reference in a new issue